Machine Learning Methods for the Analysis of the Patch-Clamp Signals.

Patch-clamp technique provides a unique possibility to record the ion channels' activity. This method enables tracking the changes in their functional states at controlled conditions on a real-time scale. Kinetic parameters evaluated for the patch-clamp signals form the fundamentals of electrophysiological characteristics of the channel functioning. Nevertheless, the noisy series of ionic currents flowing through the channel protein(s) seem to be bountiful of information, and the standard data processing techniques likely unravel only its part. Rapid development of artificial intelligence (AI) techniques, especially machine learning (ML), gives new prospects for whole channelology. Here we consider the question of the AI applications in the patch-clamp signal analysis. It turns out that the AI methods may not only enable for automatizing of signal analysis, but also they can be used in finding inherent patterns of channel gating and allow the researchers to uncover the details of gating machinery, which had been never considered before. In this work, we outline the currently known AI methods that turned out to be utilizable and useful in the analysis of patch-clamp signals. This chapter can be considered an introductory guide to the application of AI methods in the analysis of the time series of channel currents (together with its advantages, disadvantages, and limitations), but we also propose new possible directions in this field.

The cross-correlation-based analysis to digest the conformational dynamics of the mitoBK channels in terms of their modulation by flavonoids.

The activity of mitochondrial large-conductance voltage- and [Formula: see text]-activated [Formula: see text] channels (mitoBK) is regulated by a number of biochemical factors, including flavonoids. In particular, naringenin (Nar) and quercetin (Que) reached reasonable scientific attention due to their well-pronounced channel-activating effects. The open-reinforcing outcomes of Nar and Que on the mitoBK channel gating have been already reported. Nevertheless, the molecular picture of the corresponding channel-ligand interactions remains still to be revealed. In this work, we investigate the effects of the Nar and Que on the conformational dynamics of the mitoBK channel. In this aim, the cross-correlation-based analysis of the single-channel signals recorded by the patch-clamp method is performed. The obtained results in the form of phase space diagrams enable us to visually monitor the effects exerted by the considered flavonoids at the level of temporal characteristics of repetitive sequences of channel conformations. It turns out that the mitoBK channel activation by naringenin and quercetin does not lead to the change in the number of clusters within the phase space diagrams, which can be related to the constant number of available channel macroconformations regardless of the flavonoid administration. The localization and occupancy of the clusters of cross-correlated sequences suggest that mitoBK channel stimulation by flavonoids affects the relative stability of channel conformations and the kinetics of switching between them. For most clusters, greater net effects are observed in terms of quercetin administration in comparison with naringenin. It indicates stronger channel interaction with Que than Nar.

Potassium Channels, Glucose Metabolism and Glycosylation in Cancer Cells.

Potassium channels emerge as one of the crucial groups of proteins that shape the biology of cancer cells. Their involvement in processes like cell growth, migration, or electric signaling, seems obvious. However, the relationship between the function of K+ channels, glucose metabolism, and cancer glycome appears much more intriguing. Among the typical hallmarks of cancer, one can mention the switch to aerobic glycolysis as the most favorable mechanism for glucose metabolism and glycome alterations. This review outlines the interconnections between the expression and activity of potassium channels, carbohydrate metabolism, and altered glycosylation in cancer cells, which have not been broadly discussed in the literature hitherto. Moreover, we propose the potential mediators for the described relations (e.g., enzymes, microRNAs) and the novel promising directions (e.g., glycans-orinented drugs) for further research.

Non-Monotonic Complexity of Stochastic Model of the Channel Gating Dynamics.

The simple model of an ionic current flowing through a single channel in a biological membrane is used to depict the complexity of the corresponding empirical data underlying different internal constraints and thermal fluctuations. The residence times of the channel in the open and closed states are drawn from the exponential distributions to mimic the characteristics of the real channel system. In the selected state, the dynamics are modeled by the overdamped Brownian particle moving in the quadratic potential. The simulated data allow us to directly track the effects of temperature (signal-to-noise ratio) and the channel's energetic landscape for conformational changes on the ionic currents' complexity, which are hardly controllable in the experimental case. To accurately describe the randomness, we employed four quantifiers, i.e., Shannon, spectral, sample, and slope entropies. We have found that the Shannon entropy predicts the anticipated reaction to the imposed modification of randomness by raising the temperature (an increase of entropy) or strengthening the localization (reduction of entropy). Other complexity quantifiers behave unpredictably, sometimes resulting in non-monotonic behaviour. Thus, their applicability in the analysis of the experimental time series of single-channel currents can be limited.

Flavonoids as Modulators of Potassium Channels.

Potassium channels are widely distributed integral proteins responsible for the effective and selective transport of K+ ions through the biological membranes. According to the existing structural and mechanistic differences, they are divided into several groups. All of them are considered important molecular drug targets due to their physiological roles, including the regulation of membrane potential or cell signaling. One of the recent trends in molecular pharmacology is the evaluation of the therapeutic potential of natural compounds and their derivatives, which can exhibit high specificity and effectiveness. Among the pharmaceuticals of plant origin, which are potassium channel modulators, flavonoids appear as a powerful group of biologically active substances. It is caused by their well-documented anti-oxidative, anti-inflammatory, anti-mutagenic, anti-carcinogenic, and antidiabetic effects on human health. Here, we focus on presenting the current state of knowledge about the possibilities of modulation of particular types of potassium channels by different flavonoids. Additionally, the biological meaning of the flavonoid-mediated changes in the activity of K+ channels will be outlined. Finally, novel promising directions for further research in this area will be proposed.

A New Method of Identifying Characteristic Points in the Impedance Cardiography Signal Based on Empirical Mode Decomposition.

The accurate detection of fiducial points in the impedance cardiography signal (ICG) has a decisive impact on the proper estimation of diagnostic parameters such as stroke volume or cardiac output. It is, therefore, necessary to find an algorithm that is able to assess their positions with great precision. The solution to this problem is, however, quite challenging with regard to the high sensitivity of the ICG technique to the noise and varying morphology of the acquired signals. The aim of this study is to propose a novel method that allows us to overcome these limitations. The developed algorithm is based on Empirical Mode Decomposition (EMD)-an effective technique for processing and analyzing various types of non-stationary signals. We find high correlations between the results obtained from the algorithm and annotated by an expert. This, in turn, implies that the difference in estimation of the diagnostic-relevant parameters is small, which suggests that the method can automatically provide precise clinical information.

Resistance Training with Blood Flow Restriction and Ocular Health: A Brief Review.

Despite the many health benefits of resistance training, it has been suggested that high-intensity resistance exercise is associated with acute increases in intraocular pressure which is a significant risk factor for the development of glaucomatous optic nerve damage. Therefore, resistance training using a variety of forms (e.g., resistance bands, free weights, weight machines, and bodyweight) may be harmful to patients with or at risk of glaucoma. An appropriate solution for such people may involve the combination of resistance training and blood flow restriction (BFR). During the last decade, the BFR (a.k.a. occlusion or KAATSU training) method has drawn great interest among health and sports professionals because of the possibility for individuals to improve various areas of fitness and performance at lower exercise intensities. In comparison to studies evaluating the efficiency of BFR in terms of physical performance and body composition changes, there is still a paucity of empirical studies concerning safety, especially regarding ocular health. Although the use of BFR during resistance training seems feasible for glaucoma patients or those at risk of glaucoma, some issues must be investigated and resolved. Therefore, this review provides an overview of the available scientific data describing the influence of resistance training combined with BFR on ocular physiology and points to further directions of research.

To what extent naringenin binding and membrane depolarization shape mitoBK channel gating-A machine learning approach.

The large conductance voltage- and Ca2+-activated K+ channels from the inner mitochondrial membrane (mitoBK) are modulated by a number of factors. Among them flavanones, including naringenin (Nar), arise as a promising group of mitoBK channel regulators from a pharmacological point of view. It is well known that in the presence of Nar the open state probability (pop) of mitoBK channels significantly increases. Nevertheless, the molecular mechanism of the mitoBK-Nar interactions remains still unrevealed. It is also not known whether the effects of naringenin administration on conformational dynamics can resemble those which are exerted by the other channel-activating stimuli. In aim to answer this question, we examine whether the dwell-time series of mitoBK channels which were obtained at different voltages and Nar concentrations (yet allowing to reach comparable pops) are discernible by means of artificial intelligence methods, including k-NN and shapelet learning. The obtained results suggest that the structural complexity of the gating dynamics is shaped both by the interaction of channel gate with the voltage sensor (VSD) and the Nar-binding site. For a majority of data one can observe stimulus-specific patterns of channel gating. Shapelet algorithm allows to obtain better prediction accuracy in most cases. Probably, because it takes into account the complexity of local features of a given signal. About 30% of the analyzed time series do not sufficiently differ to unambiguously distinguish them from each other, which can be interpreted in terms of the existence of the common features of mitoBK channel gating regardless of the type of activating stimulus. There exist long-range mutual interactions between VSD and the Nar-coordination site that are responsible for higher levels of Nar-activation (Δpop) at deeply depolarized membranes. These intra-sensor interactions are anticipated to have an allosteric nature.

New Diagnostic Tool for Ion Channel Activity Hidden Behind the Dwell-Time Correlations.

The patch-clamp technique is a powerful tool that allows for a long observation of transport protein activity in real time. Experimental traces of single-channel currents can be considered as a record of the channel's conformational switching related to its activation and gating. In this work, we present a mathematically simple method of patch-clamp data analysis that assesses the connectivity and occupancy of distinct conformational substates of the channel. The proposed approach appears to be a big step forward due to its possible applications in the determination of channel substates related to disease and in the analysis of drug-channel interactions on the level of repetitive sequences of channel conformations. This is especially important in cases when molecular dynamics docking is impossible and Markovian modeling requires ambiguous optimization tasks.

Application of Machine-Learning Methods to Recognize mitoBK Channels from Different Cell Types Based on the Experimental Patch-Clamp Results.

(1) Background: In this work, we focus on the activity of large-conductance voltage- and Ca2+-activated potassium channels (BK) from the inner mitochondrial membrane (mitoBK). The characteristic electrophysiological features of the mitoBK channels are relatively high single-channel conductance (ca. 300 pS) and types of activating and deactivating stimuli. Nevertheless, depending on the isoformal composition of mitoBK channels in a given membrane patch and the type of auxiliary regulatory subunits (which can be co-assembled to the mitoBK channel protein) the characteristics of conformational dynamics of the channel protein can be altered. Consequently, the individual features of experimental series describing single-channel activity obtained by patch-clamp method can also vary. (2) Methods: Artificial intelligence approaches (deep learning) were used to classify the patch-clamp outputs of mitoBK activity from different cell types. (3) Results: Application of the K-nearest neighbors algorithm (KNN) and the autoencoder neural network allowed to perform the classification of the electrophysiological signals with a very good accuracy, which indicates that the conformational dynamics of the analyzed mitoBK channels from different cell types significantly differs. (4) Conclusion: We displayed the utility of machine-learning methodology in the research of ion channel gating, even in cases when the behavior of very similar microbiosystems is analyzed. A short excerpt from the patch-clamp recording can serve as a "fingerprint" used to recognize the mitoBK gating dynamics in the patches of membrane from different cell types.

Dynamical diversity of mitochondrial BK channels located in different cell types.

Mitochondrial large-conductance voltage- and Ca2+-activated potassium channels (mitoBK) exhibit substantial similarities in their physiology regardless of the channel's location. Nevertheless, depending on the cell type, composition of membranes can vary, and mitoBK channels can be expressed in different splice variants as well as they can be co-assembled with different types of auxiliary ß subunits. These factors can modulate their voltage- and Ca2+-sensitivity, and single-channel current kinetics. It is still an open question to what extent the mentioned factors can affect the complexity of the conformational dynamics of the mitoBK channel gating. In this work the dynamical diversity of mitoBK channels from different cell types was unraveled by the use of nonlinear methods of analysis: multifractal detrended fluctuation analysis (MFDFA) and multiscale entropy (MSE). These techniques were applied to the experimental series of single channel currents. It turns out that the differences in the mitoBK expression systems influence gating machinery by changing the scheme of switching between the stable channel conformations, and affecting the average number of available channel conformations (this effect is visible for mitoBK channels in glioblastoma cells). The obtained results suggest also that a pathological dynamics can be represented by signals of relatively low complexity (low MSE of the mitoBK channel gating in glioblastoma).

Differences in Gating Dynamics of BK Channels in Cellular and Mitochondrial Membranes from Human Glioblastoma Cells Unraveled by Short- and Long-Range Correlations Analysis.

The large-conductance voltage- and Ca2+-activated K+ channels (BK) are encoded in humans by the Kcnma1 gene. Nevertheless, BK channel isoforms in different locations can exhibit functional heterogeneity mainly due to the alternative splicing during the Kcnma1 gene transcription. Here, we would like to examine the existence of dynamic diversity of BK channels from the inner mitochondrial and cellular membrane from human glioblastoma (U-87 MG). Not only the standard characteristics of the spontaneous switching between the functional states of the channel is discussed, but we put a special emphasis on the presence and strength of correlations within the signal describing the single-channel activity. The considered short- and long-range memory effects are here analyzed as they can be interpreted in terms of the complexity of the switching mechanism between stable conformational states of the channel. We calculate the dependencies of mean dwell-times of (conducting/non-conducting) states on the duration of the previous state, Hurst exponents by the rescaled range R/S method and detrended fluctuation analysis (DFA), and use the multifractal extension of the DFA (MFDFA) for the series describing single-channel activity. The obtained results unraveled statistically significant diversity in gating machinery between the mitochondrial and cellular BK channels.

In Search of New Therapeutics-Molecular Aspects of the PCOS Pathophysiology: Genetics, Hormones, Metabolism and Beyond.

In a healthy female reproductive system, a subtle hormonal and metabolic dance leads to repetitive cyclic changes in the ovaries and uterus, which make an effective ovulation and potential implantation of an embryo possible. However, that is not so in the case of polycystic ovary syndrome (PCOS), in which case the central mechanism responsible for entraining hormonal and metabolic rhythms during the menstrual cycle is notably disrupted. In this review we provide a detailed description of the possible scenario of PCOS pathogenesis. We begin from the analysis of how a set of genetic disorders related to PCOS leads to particular malfunctions at a molecular level (e.g., increased enzyme activities of cytochrome P450 (CYP) type 17A1 (17α-hydroxylase), 3ß-HSD type II and CYP type 11A1 (side-chain cleavage enzyme) in theca cells, or changes in the expression of aquaporins in granulosa cells) and discuss further cellular- and tissue-level consequences (e.g., anovulation, elevated levels of the advanced glycation end products in ovaries), which in turn lead to the observed subsequent systemic symptoms. Since gene-editing therapy is currently out of reach, herein special emphasis is placed on discussing what kinds of drug targets and which potentially active substances seem promising for an effective medication, acting on the primary causes of PCOS on a molecular level.

Multifractal Properties of BK Channel Currents in Human Glioblastoma Cells.

Potassium channels play an important physiological role in glioma cells. In particular, voltage- and Ca2+-activated large-conductance BK channels (gBK in gliomas) are involved in the intensive growth and extensive migrating behavior of the mentioned tumor cells; thus, they may be considered as a drug target for the therapeutic treatment of glioblastoma. To enable appropriate drug design, molecular mechanisms of gBK channel activation by diverse stimuli should be unraveled as well as the way that the specific conformational states of the channel relate to its functional properties (conducting/nonconducting). There is an open debate about the actual mechanism of BK channel gating, including the question of how the channel proteins undergo a range of conformational transitions when they flicker between nonconducting (functionally closed) and conducting (open) states. The details of channel conformational diffusion ought to have its representation in the properties of the experimental signal that describes the ion-channel activity. Nonlinear methods of analysis of experimental nonstationary series can be useful for observing the changes in the number of channel substates available from geometrical and energetic points of view at given external conditions. In this work, we analyze whether the multifractal properties of the activity of glioblastoma BK channels depend on membrane potential, and which states, conducting or nonconducting, affect the total signal to a larger extent. With this aim, we carried out patch-clamp experiments at different levels of membrane hyper- and depolarization. The obtained time series of single channel currents were analyzed using the multifractal detrended fluctuation analysis (MFDFA) method in a standard form and incorporating focus-based multifractal (FMF) formalism. Thus, we show the applicability of a modified MFDFA technique in the analysis of an experimental patch-clamp time series. The obtained results suggest that membrane potential strongly affects the conformational space of the gBK channel proteins and the considered process has nonlinear multifractal characteristics. These properties are the inherent features of the analyzed signals due to the fact that the main tendencies vanish after shuffling the data.

The distribution of information for sEMG signals in the rectal cancer treatment process.

The electrical activity of external anal sphincter can be registered with surface electromyography. This signals are known to be highly complex and nonlinear. This work aims in characterisation of the information carried in the signals by harvesting the concept of information entropy. We will focus of two classical measures of the complexity. Firstly the Shannon entropy is addressed. It is related to the probability spectrum of the possible states. Secondly the Spectral entropy is described, as a simple frequency-domain analog of the time-domain Shannon characteristics. We discuss the power spectra for separate time scales and present the characteristics which can represent the dynamics of electrical activity of this specific muscle group. We find that the rest and maximum contraction states represent rather different spectral characteristic of entropy, with close-to-normal contraction and negatively skewed rest state.

Upper extremity surface electromyography signal changes after laparoscopic training.

INTRODUCTION: Objective measures of laparoscopic skill in training are lacking. AIM: To evaluate the changes in the surface electromyography (sEMG) signal during laparoscopic training, and to link them to intracorporeal knot tying. MATERIAL AND METHODS: Ten right-handed medical students (6 female), aged 25 ±0.98, without training in laparoscopy, were enrolled in the study. With no additional training, they tied intracorporeal single knots for 15 min. Then underwent laparoscopic training and redid the knot tying exercise. During both events, sEMG was recorded from 8 measurement points on the upper extremities and neck bilaterally. We analyzed changes in sEMG resulting from training and tried to find sEMG predictive parameters for higher technical competence defined by the number of knots tied after the training. RESULTS: The average number of knots increased after the training. Significant decreases in activity after the training were visible for the non-dominant hand deltoid and trapezius muscles. Dominant and non-dominant hands had different activation patterns. Differences largely disappeared after the training. All muscles, except for the dominant forearm and non-dominant thenar, produced a negative correlation between their activities and the number of tied knots. The strongest anticorrelation occurred for the non-dominant deltoid (r = -0.863, p < 0.05). Relatively strong relationships were identified in the case of the non-dominant trapezius and forearm muscles (r = -0.587, r = -0.504). CONCLUSIONS: At least for some muscle groups there is a change in activation patterns after laparoscopic training. Proximal muscle groups tend to become more relaxed and the distal ones become more active. Changes in the non-dominant hand are more pronounced than in the dominant hand.

Mechanosensitivity of the BK Channels in Human Glioblastoma Cells: Kinetics and Dynamical Complexity.

BK channels are potassium selective and exhibit large single-channel conductance. They play an important physiological role in glioma cells: they are involved in cell growth and extensive migrating behavior. Due to the fact that these processes are accompanied by changes in membrane stress, here, we examine mechanosensitive properties of BK channels from human glioblastoma cells (gBK channels). Experiments were performed by the use of patch-clamp method on excised patches under membrane suction (0-40 mmHg) at membrane hyper- and depolarization. We have also checked whether channel's activity is affected by possible changes of membrane morphology after a series of long impulses of suction. Unconventionally, we also analyzed internal structure of the experimental signal to make inferences about conformational dynamics of the channel in stressed membranes. We examined the fractal long-range memory effect (by R/S Hurst analysis), the rate of changes in information by sample entropy, or correlation dimension, and characterize its complexity over a range of scales by the use of Multiscale Entropy method. The obtained results indicate that gBK channels are mechanosensitive at membrane depolarization and hyperpolarization. Prolonged suction of membrane also influences open-closed fluctuations-it decreases channel's activity at membrane hyperpolarization and, in contrary, increases channel's activity at high voltages. Both membrane strain and its "fatigue" reduce dynamical complexity of channel gating, which suggest decrease in the number of available open conformations of channel protein in stressed membranes.

Multifractal characteristics of external anal sphincter based on sEMG signals.

Up to 40% of patients treated for rectal cancer suffer from therapy-related symptoms. Innervation injury is one of the suggested pathomechanisms of those symptoms hence the development of a valid, non-invasive tool for the assessment of neural systems is crucial. The aim of this work is to study the fractal properties of the surface electromyography signals obtained from patients suffering from rectal cancer. The anal sphincter activity was investigated for the group of 15 patients who underwent surgical treatment. Multifractal detrended fluctuation analysis was implemented to analyze the data, obtained at four different stages: one before treatment and three times after the surgery. The results from the standard detrended fluctuation analysis and empirical mode decomposition methods are presented and compared. The statistically significant differences between the stages of treatment were identified for the selected spectral parameters: width and maximum of the spectrum.

Sample Entropy of sEMG Signals at Different Stages of Rectal Cancer Treatment.

Information theory provides a spectrum of nonlinear methods capable of grasping an internal structure of a signal together with an insight into its complex nature. In this work, we discuss the usefulness of the selected entropy techniques for a description of the information carried by the surface electromyography signals during colorectal cancer treatment. The electrical activity of the external anal sphincter can serve as a potential source of knowledge of the actual state of the patient who underwent a common surgery for rectal cancer in the form of anterior or lower anterior resection. The calculation of Sample entropy parameters has been extended to multiple time scales in terms of the Multiscale Sample Entropy. The specific values of the entropy measures and their dependence on the time scales were analyzed with regard to the time elapsed since the operation, the type of surgical treatment and also the different depths of the rectum canal. The Mann-Whitney U test and Anova Friedman statistics indicate the statistically significant differences among all of stages of treatment and for all consecutive depths of rectum area for the estimated Sample Entropy. The further analysis at the multiple time scales signify the substantial differences among compared stages of treatment in the group of patients who underwent the lower anterior resection.

Correlation based analysis of sEMG signals during complex muscle activity. Feasibility study of new methodology.

Assessment of complex motor task (CMT) competency is still very prone to bias. Objective assessment is based either on outcomes leaving the process out of the equitation or on checklists with all their limitations. We tested the hypothesis that muscular recruitment patterns assessed with surface Electromyography (sEMG) will be different between novices and skilled trainees. sEMG signals of the muscles that potentially are characterized by the highest level of engagement at complex motor task were submitted to comprehensive correlation analysis. Standard methods of estimating the correlation coefficients were compared with more advanced analysis including cross-wavelet coherence and calculation of mutual information. We conclude that with appropriate analytical tools it is possible to compare sEMG signals during complex motor tasks and that at least on our very small sample it differs between individuals.